Outdoor-cat owners know all too well the unpleasantries of dealing with what the cat dragged in. A self-proclaimed machine learning novice proves that you don't need to be a pro to set up a smart cat door that prevents the cat from bringing prey into your home.

We take a deep dive into the poster child for black-box machine learning methods, namely Deep Patient: an unsupervised learning method that uses denoising auto-encoders as the means for extracting salient features in electronic health records, which in turn can then be used to predict health outcomes. We do our best to explain what on earth the previous sentence meant.

In this episode, we talk about how a statistical concept that you would learn about in an introductory course was misused in court.  The error led to dire consequences in the case of Sally Clark who was charged in the deaths of two of her children.

In this episode, we talk about Susan's new job as a Data Scientist!  She recently transitioned from academia to industry and we discuss her experience with searching for positions, interviewing, and her first few weeks in her new role.

In this episode, we talk about some machine learning startups to pay attention to this year.

Deep learning has been useful for lots of applications when it comes to prediction. Yet another is the use of a short sound clip of speech to predict the face of the speaker. 

In this episode, we talk about protecting kids' digital privacy.

Statistics is key to demonstrating the effectiveness of new advancements in science and medicine, but when statistical significance is not achieved, is post-hoc power a valid justification? 

In this episode, we talk about Amazon's 3D body scan study.  

In this episode, we talk about how data are personal for those in a rural Pennsylvania community.